JP2021104564A - Thermal displacement correction device - Google Patents

Thermal displacement correction device Download PDF

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JP2021104564A
JP2021104564A JP2019237228A JP2019237228A JP2021104564A JP 2021104564 A JP2021104564 A JP 2021104564A JP 2019237228 A JP2019237228 A JP 2019237228A JP 2019237228 A JP2019237228 A JP 2019237228A JP 2021104564 A JP2021104564 A JP 2021104564A
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temperature
thermal displacement
machine
unit
acquisition unit
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JP7481112B2 (en
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政信 嶽本
Masanobu Takemoto
政信 嶽本
啓太 羽田
Keita Hada
啓太 羽田
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Fanuc Corp
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Priority to KR1020200174741A priority patent/KR20210083176A/en
Priority to US17/120,261 priority patent/US11660692B2/en
Priority to DE102020134496.1A priority patent/DE102020134496A1/en
Priority to TW109145197A priority patent/TW202138089A/en
Priority to CN202011530728.7A priority patent/CN113050539A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q15/00—Automatic control or regulation of feed movement, cutting velocity or position of tool or work
    • B23Q15/007—Automatic control or regulation of feed movement, cutting velocity or position of tool or work while the tool acts upon the workpiece
    • B23Q15/18—Compensation of tool-deflection due to temperature or force
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23H—WORKING OF METAL BY THE ACTION OF A HIGH CONCENTRATION OF ELECTRIC CURRENT ON A WORKPIECE USING AN ELECTRODE WHICH TAKES THE PLACE OF A TOOL; SUCH WORKING COMBINED WITH OTHER FORMS OF WORKING OF METAL
    • B23H11/00—Auxiliary apparatus or details, not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23H—WORKING OF METAL BY THE ACTION OF A HIGH CONCENTRATION OF ELECTRIC CURRENT ON A WORKPIECE USING AN ELECTRODE WHICH TAKES THE PLACE OF A TOOL; SUCH WORKING COMBINED WITH OTHER FORMS OF WORKING OF METAL
    • B23H7/00—Processes or apparatus applicable to both electrical discharge machining and electrochemical machining
    • B23H7/02—Wire-cutting
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23H—WORKING OF METAL BY THE ACTION OF A HIGH CONCENTRATION OF ELECTRIC CURRENT ON A WORKPIECE USING AN ELECTRODE WHICH TAKES THE PLACE OF A TOOL; SUCH WORKING COMBINED WITH OTHER FORMS OF WORKING OF METAL
    • B23H7/00—Processes or apparatus applicable to both electrical discharge machining and electrochemical machining
    • B23H7/14—Electric circuits specially adapted therefor, e.g. power supply
    • B23H7/20—Electric circuits specially adapted therefor, e.g. power supply for programme-control, e.g. adaptive
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q11/00—Accessories fitted to machine tools for keeping tools or parts of the machine in good working condition or for cooling work; Safety devices specially combined with or arranged in, or specially adapted for use in connection with, machine tools
    • B23Q11/0003—Arrangements for preventing undesired thermal effects on tools or parts of the machine
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/22—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring existing or desired position of tool or work
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/404—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/35—Nc in input of data, input till input file format
    • G05B2219/35015—Calculate production compensation, heat shrinkage, overetching
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/45—Nc applications
    • G05B2219/45043—EDM machine, wire cutting
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/49—Nc machine tool, till multiple
    • G05B2219/49206—Compensation temperature, thermal displacement, use measured temperature
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/49—Nc machine tool, till multiple
    • G05B2219/49307—Learn, learn operational zone, feed, speed to avoid tool breakage

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  • Automation & Control Theory (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

To provide a technique for reducing labor and time required for learning work when performing thermal displacement correction in an electric spark machine using a machine learning technique.SOLUTION: A thermal displacement correction device 1 comprises: a temperature acquisition unit 110 for measuring a temperature of an environment in which a machine is installed and a temperature of each part of the machine; a thermal displacement amount acquisition unit 130 for acquiring a thermal displacement amount of the machine; a temperature difference calculation unit 120 for calculating a temperature difference between at least two temperatures of temperatures measured by the temperature acquisition unit 110; and a learning unit 140 for generating a thermal displacement correction model for estimating output data from input data by machine learning on the basis of teacher data which takes as the input data the temperatures measured by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation part 120 and which outputs the thermal displacement amount acquired by the thermal displacement amount acquisition unit 130 as the output data.SELECTED DRAWING: Figure 2

Description

本発明は、熱変位補正装置に関し、特に放電加工機における熱変位補正装置に関する。 The present invention relates to a thermal displacement compensator, and more particularly to a thermal displacement compensator in an electric discharge machine.

図４は、放電加工機の一種であるワイヤ放電加工機の概略構成図である。ワイヤ放電加工機３００は、機台３０１の上の加工槽３０２内に載置された図示しないワークを、ワイヤ電極３０４により加工する。機台３０１の奥端に立てられたコラム３０３の上部には、ワイヤ電極３０４が巻かれたワイヤボビン３１１が取り付けられている。ワイヤボビン３１１は、送り出し部トルクモータ３１０により、ワイヤ電極３０４の引き出し方向とは逆方向に指令された所定低トルクが付与される。ワイヤボビン３１１から繰り出されたワイヤ電極３０４は、ブレーキモータ３１２により駆動されるブレーキシュー３１３、上ガイドローラ３１４、上ガイド３１５に備えられた上ワイヤ支持ガイド３１６、下ガイド３１７に備えられた下ワイヤ支持ガイド３１８、下ガイドローラ３１９を経由して、フィードローラ３２２に掛け回される。ブレーキモータ３１２により駆動されるブレーキシュー３１３とワイヤ電極送りモータ（図示せず）で駆動されるフィードローラ３２２の間の張力が調節される。ワイヤ電極３０４は、ピンチローラ３２１とワイヤ電極送りモータ（図示せず）で駆動されるフィードローラ３２２で挟まれ、ワイヤ電極回収箱３２０に回収される。機台３０１上の加工槽３０２内にはワークを載置するテーブルが取り付けられている。上ガイド３１５と下ガイド３１７の間の放電加工領域には放電加工対象となる図示しないワークが図示しないテーブルに載置され、ワイヤ電極３０４に加工用電源から高周波電圧が印加され放電加工がなされる。 FIG. 4 is a schematic configuration diagram of a wire electric discharge machine, which is a type of electric discharge machine. The wire electric discharge machine 300 processes a work (not shown) placed in the processing tank 302 on the machine base 301 by the wire electrode 304. A wire bobbin 311 around which a wire electrode 304 is wound is attached to an upper portion of a column 303 erected at the back end of the machine base 301. The wire bobbin 311 is subjected to a predetermined low torque commanded in the direction opposite to the pull-out direction of the wire electrode 304 by the feeding portion torque motor 310. The wire electrode 304 unwound from the wire bobbin 311 is a brake shoe 313 driven by a brake motor 312, an upper guide roller 314, an upper wire support guide 316 provided on the upper guide 315, and a lower wire support provided on the lower guide 317. It is hung on the feed roller 322 via the guide 318 and the lower guide roller 319. The tension between the brake shoe 313 driven by the brake motor 312 and the feed roller 322 driven by the wire electrode feed motor (not shown) is adjusted. The wire electrode 304 is sandwiched between a pinch roller 321 and a feed roller 322 driven by a wire electrode feed motor (not shown), and is collected in a wire electrode collection box 320. A table on which the work is placed is installed in the processing tank 302 on the machine base 301. In the electric discharge machining region between the upper guide 315 and the lower guide 317, a workpiece (not shown) to be electric discharge machined is placed on a table (not shown), and a high frequency voltage is applied to the wire electrode 304 from a machining power source to perform electric discharge machining. ..

このように、放電加工機は、様々な機械要素が組み合わされて構成されている。これら機械要素は、それぞれ熱膨張率が異なっている。そのため、周囲の気温の変化や、図示しない放電電源装置の発熱、放電加工時のアーク放電による発熱、加工液を循環させるための図示しないポンプの発熱等により機械要素の温度が上昇して熱変形すると、機械要素間の相対的な位置・姿勢にずれが生じる。このずれは電極とワークとの間の位置関係に影響を及ぼし、加工精度の低下の原因となる。 As described above, the electric discharge machine is configured by combining various mechanical elements. These mechanical elements have different coefficients of thermal expansion. Therefore, the temperature of the machine element rises due to changes in the ambient temperature, heat generation of a discharge power supply device (not shown), heat generation due to arc discharge during electric discharge machining, heat generation of a pump (not shown) for circulating machining fluid, etc., resulting in thermal deformation. Then, the relative position / orientation between the machine elements is deviated. This deviation affects the positional relationship between the electrode and the work, and causes a decrease in machining accuracy.

加工精度の低下を防止するために、放電加工機の各部の温度を測定し、測定された温度に基づいて熱変位量を補正することが行われている。図４に例示されるワイヤ放電加工機３００では、例えばコラム３０３の上部の温度や加工槽３０２内の加工液の水温、機械周辺の室温を測定する。そして、測定された温度に基づいて上ガイド３１５、下ガイド３１７の熱変位量を予測し、上ガイド３１５の位置と下ガイド３１７の位置を補正する。 In order to prevent a decrease in machining accuracy, the temperature of each part of the electric discharge machine is measured, and the amount of thermal displacement is corrected based on the measured temperature. In the wire electric discharge machine 300 illustrated in FIG. 4, for example, the temperature of the upper part of the column 303, the water temperature of the machining liquid in the machining tank 302, and the room temperature around the machine are measured. Then, the amount of thermal displacement of the upper guide 315 and the lower guide 317 is predicted based on the measured temperature, and the positions of the upper guide 315 and the lower guide 317 are corrected.

熱変位量の予測を行う方法の一つとして、機械学習を用いる方法が知られている（例えば、特許文献１等）。機械学習を用いて熱変位量の予測を行う場合、例えば熱変位補正モデルを作成し、該モデルのパラメータを機械学習で学習する方法がある。上記のワイヤ放電加工機の例では、例えば以下の数１式を熱変位補正モデルとして用いることができる。数１式において、Ｄu及びＤlはそれぞれ上ガイド、下ガイドの変位量、Ｃu、Ｃw、Ｃlはそれぞれコラム３０３の上部の温度、加工槽３０２内の加工液の水温、機械周辺の室温、ａ１u〜ａ３u、ａ１l〜ａ３lはワイヤ放電加工機の種類や動作環境によって定まる係数である。 As one of the methods for predicting the amount of thermal displacement, a method using machine learning is known (for example, Patent Document 1 and the like). When predicting the amount of thermal displacement using machine learning, for example, there is a method of creating a thermal displacement correction model and learning the parameters of the model by machine learning. In the above example of the wire electric discharge machine, for example, the following equation 1 can be used as a thermal displacement correction model. In the equation 1, D u and D l are the displacement amounts of the upper guide and the lower guide, respectively, and Cu , C w , and C l are the temperature of the upper part of the column 303, the water temperature of the machining fluid in the machining tank 302, and the periphery of the machine, respectively. Room temperature, a1 u to a3 u , and a1 l to a3 l are coefficients determined by the type of wire electric discharge machine and the operating environment.

Figure 2021104564
Figure 2021104564

機械学習においては、部屋の温度を変化させたり、ワイヤ放電加工機を運転しながら、各部の温度と熱変位量を測定する。そして、測定した変位量と、測定した温度を数１式に当てはめた場合に算出される変位量との差が最小となるように（例えば、最小二乗法等で）係数を決定する。係数が決定された数１式を用いることで、所定の温度が測定されたときの補正量を推定できるので、推定された補正量に基づいて上ガイド位置、下ガイド位置を補正できるようになる。 In machine learning, the temperature of each part and the amount of thermal displacement are measured while changing the temperature of the room or operating the wire electric discharge machine. Then, the coefficient is determined so that the difference between the measured displacement amount and the displacement amount calculated when the measured temperature is applied to the equation 1 is minimized (for example, by the method of least squares or the like). Since the correction amount when a predetermined temperature is measured can be estimated by using the equation 1 in which the coefficient is determined, the upper guide position and the lower guide position can be corrected based on the estimated correction amount. ..

特開２０１８−０６９４０８号公報Japanese Unexamined Patent Publication No. 2018-069408

機械学習の技術を用いて放電加工機の熱変位補正を行う場合、様々な環境の状態に適応できる熱変位補正モデルを作成し、様々な環境の状態を考慮したデータを測定した上で、それらを教師データとした学習を行う必要がある。しかしながら、放電加工機の環境を定める条件は様々であり、すべての環境に適応できるように機械学習を行うには大きな労力が掛かる。 When performing thermal displacement correction of a discharge machine using machine learning technology, create a thermal displacement correction model that can be adapted to various environmental conditions, measure data that takes into account various environmental conditions, and then use them. It is necessary to perform learning using the teacher data. However, there are various conditions that determine the environment of an electric discharge machine, and it takes a lot of labor to perform machine learning so that it can be adapted to all environments.

例えば、放電加工機による加工では、ワークを切断する場合には、放電に掛けるパワーを強く設定した荒加工を行う。この場合、加工液ポンプや放電により発生する発熱は大きくなるため、加工液の水温が大きく上昇する。また、切断したワークの切断面をならす加工をする場合には、放電に掛けるパワーを抑え目に設定した仕上げ加工を行う。この場合、加工液ポンプや放電により発生する発熱は荒加工よりも小さくなり、加工液の水温の上昇も小さくなる。また、加工をしていない非加工時の場合は加工による水温上昇は殆ど見られない。 For example, in machining with an electric discharge machine, when cutting a workpiece, rough machining is performed in which the power applied to the electric discharge is strongly set. In this case, the heat generated by the machining fluid pump and the electric discharge becomes large, so that the water temperature of the machining fluid rises significantly. Further, when the cut surface of the cut work is smoothed, the power applied to the discharge is suppressed and the finishing process is performed. In this case, the heat generated by the machining fluid pump and the electric discharge is smaller than that in rough machining, and the rise in the water temperature of the machining fluid is also smaller. In addition, in the case of non-processing, which is not processed, the water temperature does not rise due to processing.

一方で、ワイヤ放電加工機３００の加工槽３０２に供給される加工液は、図示しない加工液冷却装置により水温管理されている。この加工液冷却装置は、加工液の水温を機械周辺の室温と同値となるように水温管理する。図５は、部屋の空調の設定を変化させた場合の、機械周辺の室温と加工液の水温の変化をグラフとして示したものである。図５に例示されるように、室温が低下する時（図中Ａ）は、加工液の水温は加工液冷却装置により機械周辺の室温に追従するように冷やされる。しかしながら、室温が上昇する時（図中Ｂ）は、加工液冷却装置は加工液を温める機能を備えていないので、加工液の水温は機械周辺の室温に追従できない。つまり、室温が上昇する時に、加工液の水温を機械周辺の室温に追従させるには、加工液冷却装置以外の効果により加工液を暖める必要がある。 On the other hand, the water temperature of the machining fluid supplied to the machining tank 302 of the wire electric discharge machine 300 is controlled by a machining fluid cooling device (not shown). This machining fluid cooling device manages the water temperature of the machining fluid so that it becomes the same value as the room temperature around the machine. FIG. 5 is a graph showing changes in the room temperature around the machine and the water temperature of the processing liquid when the air conditioning setting in the room is changed. As illustrated in FIG. 5, when the room temperature drops (A in the figure), the water temperature of the machining fluid is cooled by the machining fluid cooling device so as to follow the room temperature around the machine. However, when the room temperature rises (B in the figure), the machining fluid cooling device does not have a function of warming the machining fluid, so that the water temperature of the machining fluid cannot follow the room temperature around the machine. That is, in order to make the water temperature of the machining fluid follow the room temperature around the machine when the room temperature rises, it is necessary to warm the machining fluid by an effect other than the machining fluid cooling device.

この加工液冷却装置による水温管理の性質により、発熱が大きい荒加工をしている場合と、発熱が小さい仕上げ加工をしている場合や加工をしていない場合とで、放電加工機の環境が異なってくる場合がある。即ち、荒加工をしている場合には発熱により加工液が温められるため、機械周辺の室温が上昇した場合に加工液の水温を追従させることができる。しかしながら、仕上げ加工をしている場合や加工をしていない場合には、発熱が小さく加工液が十分に温められていないため、機械周辺の室温に加工液の水温が追従しにくくなる。 Due to the nature of water temperature control by this machining fluid cooling device, the environment of the electric discharge machine can be changed depending on whether rough machining is performed with large heat generation, finish machining with low heat generation is performed, or processing is not performed. It may be different. That is, in the case of rough machining, the machining fluid is heated by heat generation, so that the water temperature of the machining fluid can be followed when the room temperature around the machine rises. However, when finishing or not processing, the heat generation is small and the processing liquid is not sufficiently warmed, so that it becomes difficult for the water temperature of the processing liquid to follow the room temperature around the machine.

そのため、機械学習を行う際には、荒加工をしている場合と、仕上げ加工をしている場合や非加工時の場合とで、それぞれ各部の温度と熱変位量の測定を行い、それぞれの教師データを作成して学習に用いる必要がある。一方の環境において測定して得られた教師データだけでは、他方の環境において精度良く熱変位量を推定するモデルが作成できないためである。しかしながら、このようなデータ測定の作業は作業者に多大な負担をかけることとなる。
そこで、上記したような機械学習の技術を用いて放電加工機における熱変位補正を行う際に、学習作業に掛ける労力を軽減することを可能とする技術が望まれている。 Therefore, when performing machine learning, the temperature and thermal displacement of each part are measured in the case of rough machining, the case of finishing machining, and the case of non-machining, respectively. It is necessary to create teacher data and use it for learning. This is because it is not possible to create a model that accurately estimates the amount of thermal displacement in the other environment using only the teacher data obtained by measuring in one environment. However, such data measurement work imposes a great burden on the operator.
Therefore, there is a demand for a technique capable of reducing the labor required for learning work when performing thermal displacement correction in an electric discharge machine using the above-mentioned machine learning technique.

本発明の熱変位補正装置は、熱変位補正量の学習及び推定を行うデータとして、所定の部分間の温度の差を用いることで上記課題を解決する。例えば、数１式に例示されるような熱変位補正モデルの式に対して、更に機械周辺の室温とその追従先の温度（上記例では水温）との差に係数を掛けた項を設ける。 The thermal displacement correction device of the present invention solves the above problem by using the temperature difference between predetermined portions as data for learning and estimating the thermal displacement correction amount. For example, in addition to the equation of the thermal displacement correction model as illustrated in Equation 1, a term is provided in which the difference between the room temperature around the machine and the temperature of the follow-up destination (water temperature in the above example) is multiplied by a coefficient.

そして、本発明の一態様は、複数の機械要素が組み合わされて構成される機械の熱変位を補正する熱変位補正に係る機能を有する熱変位補正に係る装置であって、前記機械が設置された環境の温度及び前記機械の各部の温度を測定する温度取得部と、前記機械の熱変位量を取得する熱変位量取得部と、前記温度取得部が測定した温度の内で、少なくとも２つの温度の温度差を算出する温度差算出部と、前記温度取得部が測定した温度と、前記温度差算出部が算出した温度差とを入力データとし、前記熱変位量取得部が取得した熱変位量を出力データとする教師データに基づいて、前記入力データから前記出力データを推定する熱変位補正モデルを機械学習により作成する学習部と、を備えた熱変位補正に係る装置である。 Then, one aspect of the present invention is a device related to thermal displacement correction having a function related to thermal displacement correction for correcting the thermal displacement of a machine configured by combining a plurality of mechanical elements, and the machine is installed. At least two of the temperature acquisition unit that measures the temperature of the environment and the temperature of each part of the machine, the thermal displacement amount acquisition unit that acquires the thermal displacement amount of the machine, and the temperature measured by the temperature acquisition unit. The temperature difference calculation unit that calculates the temperature difference of the temperature, the temperature measured by the temperature acquisition unit, and the temperature difference calculated by the temperature difference calculation unit are used as input data, and the heat displacement acquired by the heat displacement amount acquisition unit. It is a device related to thermal displacement correction including a learning unit that creates a thermal displacement correction model that estimates the output data from the input data by machine learning based on teacher data having a quantity as output data.

本発明の他の態様は、複数の機械要素が組み合わされて構成される機械の熱変位を補正する熱変位補正機能を有する熱変位補正装置であって、前記機械が設置された環境の温度及び前記機械の各部の温度を測定する温度取得部と、を取得する熱変位量取得部と、前記温度取得部が測定した温度の内で少なくとも２つの温度の温度差を算出する温度差算出部と、前記機械が設置された環境の温度及び前記機械の各部の温度と、前記環境の温度及び前記機械の各部の温度の内で少なくとも２つの温度から算出された温度差とを入力データとし、前記機械の熱変位量を出力データとする教師データに基づいて機械学習をすることで作成された熱変位補正モデルを記憶する学習モデル記憶部と、前記温度取得部が測定した温度と、前記温度差算出部が算出した温度差とに基づいて、前記学習モデル記憶部に記憶される熱変位補正モデルを用いた前記機械の熱変位量の推定をする推定部と、前記推定部の推定結果に基づいて、前記機械の熱変位を補正する補正部と、を備えた熱変位補正装置である。 Another aspect of the present invention is a thermal displacement correction device having a thermal displacement correction function for correcting the thermal displacement of a machine configured by combining a plurality of mechanical elements, such as the temperature of the environment in which the machine is installed and the temperature of the environment in which the machine is installed. A temperature acquisition unit that measures the temperature of each part of the machine, a thermal displacement amount acquisition unit that acquires the temperature, and a temperature difference calculation unit that calculates the temperature difference of at least two temperatures among the temperatures measured by the temperature acquisition unit. , The temperature of the environment in which the machine is installed and the temperature of each part of the machine, and the temperature difference calculated from at least two temperatures within the temperature of the environment and the temperature of each part of the machine are used as input data. A learning model storage unit that stores a thermal displacement correction model created by performing machine learning based on teacher data that uses the amount of thermal displacement of a machine as output data, a temperature measured by the temperature acquisition unit, and the temperature difference. Based on the temperature difference calculated by the calculation unit, the estimation unit that estimates the thermal displacement amount of the machine using the thermal displacement correction model stored in the learning model storage unit, and the estimation result of the estimation unit. This is a thermal displacement correction device including a correction unit for correcting the thermal displacement of the machine.

本発明の一態様により、機械学習の技術を用いて放電加工機における熱変位補正を行う際に、学習作業に掛ける労力を軽減することが可能となる。 According to one aspect of the present invention, it is possible to reduce the labor required for learning work when performing thermal displacement correction in an electric discharge machine using a machine learning technique.

一実施形態による熱変位補正装置の概略的なハードウェア構成図である。It is a schematic hardware block diagram of the thermal displacement correction apparatus by one Embodiment. 第１実施形態による熱変位補正装置の機能を示す概略的なブロック図である。It is a schematic block diagram which shows the function of the thermal displacement correction apparatus by 1st Embodiment. 第２実施形態による熱変位補正装置の機能を示す概略的なブロック図である。It is a schematic block diagram which shows the function of the thermal displacement correction apparatus by 2nd Embodiment. ワイヤ放電加工機の概略構成図である。It is a schematic block diagram of a wire electric discharge machine. 部屋の空調の設定を変化させた場合の、機械周辺の室温と加工液の水温の変化を示すグラフである。It is a graph which shows the change of the room temperature around the machine and the water temperature of the processing liquid when the setting of the air conditioning of a room is changed. ニューラルネットワークを用いて学習モデルを構築する例を示す図である。の変化を示すグラフである。It is a figure which shows an example of constructing a learning model using a neural network. It is a graph which shows the change of.

以下、本発明の実施形態を図面と共に説明する。
図１は本発明の一実施形態による熱変位補正装置の要部を示す概略的なハードウェア構成図である。本発明の熱変位補正装置１は、例えば制御用プログラムに基づいて放電加工機などの産業機械を制御する制御装置として実装することができる。また、本発明の熱変位補正装置１は、制御用プログラムに基づいて産業機械を制御する制御装置に併設されたパソコンや、有線／無線のネットワークを介して制御装置と接続されたパソコン、セルコンピュータ、フォグコンピュータ、クラウドサーバの上に実装することができる。本実施形態では、熱変位補正装置１を、制御用プログラムに基づいてワイヤ放電加工機を制御する制御装置として実装した例を示す。 Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a schematic hardware configuration diagram showing a main part of a thermal displacement correction device according to an embodiment of the present invention. The thermal displacement correction device 1 of the present invention can be implemented as a control device that controls an industrial machine such as an electric discharge machine based on, for example, a control program. Further, the thermal displacement correction device 1 of the present invention includes a personal computer attached to a control device that controls an industrial machine based on a control program, a personal computer connected to the control device via a wired / wireless network, and a cell computer. , Fog computer, can be implemented on cloud server. In this embodiment, an example in which the thermal displacement correction device 1 is mounted as a control device that controls a wire electric discharge machine based on a control program is shown.

本実施形態による熱変位補正装置１が備えるＣＰＵ１１は、熱変位補正装置１を全体的に制御するプロセッサである。ＣＰＵ１１は、バス２２を介してＲＯＭ１２に格納されたシステム・プログラムを読み出し、該システム・プログラムに従って熱変位補正装置１全体を制御する。ＲＡＭ１３には一時的な計算データや表示データ、及び外部から入力された各種データ等が一時的に格納される。 The CPU 11 included in the thermal displacement correction device 1 according to the present embodiment is a processor that controls the thermal displacement correction device 1 as a whole. The CPU 11 reads the system program stored in the ROM 12 via the bus 22 and controls the entire thermal displacement correction device 1 according to the system program. Temporary calculation data, display data, various data input from the outside, and the like are temporarily stored in the RAM 13.

不揮発性メモリ１４は、例えば図示しないバッテリでバックアップされたメモリやＳＳＤ（Ｓｏｌｉｄ Ｓｔａｔｅ Ｄｒｉｖｅ）等で構成され、熱変位補正装置１の電源がオフされても記憶状態が保持される。不揮発性メモリ１４には、インタフェース１５を介して外部機器７２から読み込まれた制御用プログラムやデータ、入力装置７１を介して入力された制御用プログラムやデータ、図示しないネットワークを介して他の装置から取得された制御用プログラムやデータ等が記憶される。不揮発性メモリ１４に記憶された制御用プログラムやデータは、実行時／利用時にはＲＡＭ１３に展開されても良い。また、ＲＯＭ１２には、公知の解析プログラムなどの各種システム・プログラムがあらかじめ書き込まれている。 The non-volatile memory 14 is composed of, for example, a memory backed up by a battery (not shown), an SSD (Solid State Drive), or the like, and the storage state is maintained even when the power of the thermal displacement correction device 1 is turned off. The non-volatile memory 14 has control programs and data read from the external device 72 via the interface 15, control programs and data input via the input device 71, and from other devices via a network (not shown). The acquired control program, data, etc. are stored. The control program or data stored in the non-volatile memory 14 may be expanded in the RAM 13 at the time of execution / use. Further, various system programs such as a known analysis program are written in the ROM 12 in advance.

インタフェース１５は、熱変位補正装置１のＣＰＵ１１とＵＳＢ装置等の外部機器７２と接続するためのインタフェースである。外部機器７２側からは、例えばワイヤ放電加工機の制御に用いられる制御用プログラムや設定データ等が読み込まれる。また、熱変位補正装置１内で編集した制御用プログラムや設定データ等は、外部機器７２を介して外部記憶手段に記憶させることができる。ＰＬＣ（プログラマブル・ロジック・コントローラ）１６は、ラダープログラムを実行してワイヤ放電加工機及び該ワイヤ放電加工機の周辺装置（例えば、ワイヤ放電加工機の環境の温度や各部の温度を測定するために取付けられている温度センサ等のセンサ３）にＩ／Ｏユニット１９を介して信号を出力し制御する。また、ワイヤ放電加工機の本体に配備された操作盤の各種スイッチや周辺装置等の信号を受け、必要な信号処理をした後、ＣＰＵ１１に渡す。 The interface 15 is an interface for connecting the CPU 11 of the thermal displacement correction device 1 and an external device 72 such as a USB device. From the external device 72 side, for example, a control program and setting data used for controlling the wire electric discharge machine are read. Further, the control program, setting data, and the like edited in the thermal displacement correction device 1 can be stored in the external storage means via the external device 72. The PLC (programmable logic controller) 16 executes a ladder program to measure the wire discharge processing machine and peripheral devices of the wire discharge processing machine (for example, the temperature of the environment of the wire discharge processing machine and the temperature of each part). A signal is output and controlled via the I / O unit 19 to a sensor 3) such as a temperature sensor attached. Further, after receiving signals from various switches and peripheral devices of the operation panel provided in the main body of the wire electric discharge machine, performing necessary signal processing, the signals are passed to the CPU 11.

表示装置７０には、メモリ上に読み込まれた各データ、プログラム等が実行された結果として得られたデータ等がインタフェース１７を介して出力されて表示される。また、キーボードやポインティングデバイス等から構成される入力装置７１は、作業者による操作に基づく指令，データ等をインタフェース１８を介してＣＰＵ１１に渡す。 On the display device 70, each data read on the memory, data obtained as a result of executing a program or the like, or the like is output and displayed via the interface 17. Further, the input device 71 composed of a keyboard, a pointing device, and the like passes commands, data, and the like based on operations by the operator to the CPU 11 via the interface 18.

ワイヤ放電加工機が備える軸を制御するための軸制御回路３０はＣＰＵ１１からの軸の移動指令量を受けて、軸の指令をサーボアンプ４０に出力する。サーボアンプ４０はこの指令を受けて、工作機械が備える軸を移動させるサーボモータ５０を駆動する。軸のサーボモータ５０は位置・速度検出器を内蔵し、この位置・速度検出器からの位置・速度フィードバック信号を軸制御回路３０にフィードバックし、位置・速度のフィードバック制御を行う。なお、図１のハードウェア構成図では軸制御回路３０、サーボアンプ４０、サーボモータ５０は１つずつしか示されていないが、実際には制御対象となるワイヤ放電加工機に備えられた軸の数（例えば、Ｘ，Ｙ，Ｚ，Ｕ，Ｖの５軸）だけ用意される。 The axis control circuit 30 for controlling the axis included in the wire electric discharge machine receives the axis movement command amount from the CPU 11 and outputs the axis command to the servo amplifier 40. In response to this command, the servo amplifier 40 drives the servomotor 50 that moves the shaft included in the machine tool. The shaft servomotor 50 has a built-in position / speed detector, feeds back the position / speed feedback signal from the position / speed detector to the shaft control circuit 30, and performs position / speed feedback control. In the hardware configuration diagram of FIG. 1, only one shaft control circuit 30, a servo amplifier 40, and a servo motor 50 are shown, but in reality, the shaft provided in the wire electric discharge machine to be controlled is used. Only a number (for example, 5 axes of X, Y, Z, U, and V) are prepared.

図２は、本発明の第１実施形態による熱変位補正装置１が備える機能を概略的なブロック図として示したものである。本実施形態による熱変位補正装置１が備える各機能は、図１に示した熱変位補正装置１が備えるＣＰＵ１１がシステム・プログラムを実行し、熱変位補正装置１の各部の動作を制御することにより実現される。 FIG. 2 shows a schematic block diagram of the functions provided by the thermal displacement correction device 1 according to the first embodiment of the present invention. Each function of the thermal displacement correction device 1 according to the present embodiment is obtained by the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executing a system program and controlling the operation of each part of the thermal displacement correction device 1. It will be realized.

本実施形態の熱変位補正装置１は、制御部１００、温度取得部１１０、温度差算出部１２０、熱変位量取得部１３０、学習部１４０を備える。また、熱変位補正装置１のＲＡＭ１３乃至不揮発性メモリ１４には、予めワイヤ放電加工機を制御するための制御用プログラム２００が記憶されており、また、学習部１４０による学習に用いる学習データを記憶するための領域としての学習データ記憶部２１０、学習部１４０が作成した学習モデルを記憶するための領域としての学習モデル記憶部２２０がそれぞれ設けられている。 The thermal displacement correction device 1 of the present embodiment includes a control unit 100, a temperature acquisition unit 110, a temperature difference calculation unit 120, a thermal displacement amount acquisition unit 130, and a learning unit 140. Further, in the RAM 13 to the non-volatile memory 14 of the thermal displacement correction device 1, a control program 200 for controlling the wire discharge processing machine is stored in advance, and learning data used for learning by the learning unit 140 is stored. A learning data storage unit 210 is provided as an area for storing the learning model, and a learning model storage unit 220 is provided as an area for storing the learning model created by the learning unit 140.

制御部１００は、図１に示した熱変位補正装置１が備えるＣＰＵ１１がＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理と、軸制御回路３０、ＰＬＣ１６を用いたワイヤ放電加工機の各部の制御処理、インタフェース１８を介した入出力処理が行われることで実現される。制御部１００は、制御用プログラム２００のブロックを解析し、その解析結果に基づいてワイヤ放電加工機及びその周辺装置を制御する。制御部１００は、例えば制御用プログラム２００のブロックがワイヤ放電加工機の各軸を駆動させるように指令している場合には、ブロックによる指令に従って移動指令データを生成してサーボモータ５０に対して出力する。制御部１００は、例えば制御用プログラム２００のブロックがワイヤ電極に対して電圧を印加する指令や、加工液を循環させる指令をしている場合には、ブロックによる指令に従って放電電源装置やポンプに対して指令データを出力する。また、制御部１００は、例えば制御用プログラム２００のブロックがワイヤ放電加工機に取り付けられたセンサ３等の周辺装置を動作させるように指令している場合には、該周辺装置を動作させる所定の信号を生成してＰＬＣ１６に出力する。一方で、制御部１００は、サーボモータ５０の速度フィードバックや、温度センサ等のセンサ３で測定された温度データを取得する。 The control unit 100 executes a system program read from the ROM 12 by the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1, and mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14 by the CPU 11, and the axis control circuit 30. , The control process of each part of the wire discharge processing machine using the PLC 16 and the input / output process via the interface 18 are performed. The control unit 100 analyzes the block of the control program 200 and controls the wire electric discharge machine and its peripheral device based on the analysis result. For example, when the block of the control program 200 commands the servomotor 50 to drive each axis of the wire electric discharge machine, the control unit 100 generates movement command data according to the command from the block to the servomotor 50. Output. For example, when the block of the control program 200 gives a command to apply a voltage to the wire electrode or a command to circulate the machining fluid, the control unit 100 sends a command to the discharge power supply device or the pump according to the command from the block. And output the command data. Further, when the block of the control program 200 is instructed to operate a peripheral device such as a sensor 3 attached to the wire electric discharge machine, the control unit 100 is determined to operate the peripheral device. A signal is generated and output to the PLC 16. On the other hand, the control unit 100 acquires the speed feedback of the servomotor 50 and the temperature data measured by the sensor 3 such as the temperature sensor.

温度取得部１１０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理と、ＰＬＣ１６を用いた制御処理が行われることで実現される。温度取得部１１０は、センサ３により測定されたワイヤ放電加工機の環境の温度や各部の温度の温度データを取得する。温度取得部１１０が取得する温度データは、例えば機械周辺の室温や、コラム３０３の上部の温度や加工槽３０２内の加工液の水温を測定したものを含む。温度取得部１１０が取得した温度データは、測定された時刻と関連付けて学習データ記憶部２１０に記憶される。 In the temperature acquisition unit 110, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and the CPU 11 mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14, and the PLC16. It is realized by performing the control process using. The temperature acquisition unit 110 acquires temperature data of the environment temperature of the wire electric discharge machine and the temperature of each part measured by the sensor 3. The temperature data acquired by the temperature acquisition unit 110 includes, for example, measurements of the room temperature around the machine, the temperature of the upper part of the column 303, and the water temperature of the processing liquid in the processing tank 302. The temperature data acquired by the temperature acquisition unit 110 is stored in the learning data storage unit 210 in association with the measured time.

温度差算出部１２０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理が行われることで実現される。温度差算出部１２０は、温度取得部１１０が取得した温度データの内で、予め設定された所定の温度データの間の差を算出する。温度差算出部１２０は、例えば、加工液の水温の温度データと、機械周辺の室温の温度データとの差を算出し、算出した温度データの差を算出元の温度データと関連付けて学習データ記憶部２１０に記憶する。温度差算出部１２０が差を算出する温度データは、ワイヤ放電加工機の所定の部分で測定された温度の温度データと、該温度を調整する際に参照する先の温度の温度データとの差であることが望ましい。ワイヤ放電加工機の場合、上記で説明したように、加工液の水温は加工液冷却装置により機械周辺の室温に追従させるように調整される。そのため、このような構成を備えたワイヤ放電加工機において機械学習による熱変位補正をする場合には、温度差算出部１２０により加工液の水温の温度データと、機械周辺の室温の温度データとの差を算出すると良い。ワイヤ放電加工機の複数の部分で温度の調整が行われる場合には、温度差算出部１２０は、複数の部分の温度データの差を算出するようにしても良い。 In the temperature difference calculation unit 120, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and the CPU 11 mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14. It is realized by being struck. The temperature difference calculation unit 120 calculates the difference between the preset predetermined temperature data among the temperature data acquired by the temperature acquisition unit 110. The temperature difference calculation unit 120 calculates, for example, the difference between the temperature data of the water temperature of the processing liquid and the temperature data of the room temperature around the machine, and associates the calculated temperature data difference with the temperature data of the calculation source to store the learning data. Store in unit 210. The temperature data for which the temperature difference calculation unit 120 calculates the difference is the difference between the temperature data of the temperature measured at a predetermined part of the wire discharge processing machine and the temperature data of the destination temperature referred to when adjusting the temperature. Is desirable. In the case of a wire electric discharge machine, as described above, the water temperature of the machining fluid is adjusted by the machining fluid cooling device so as to follow the room temperature around the machine. Therefore, in the case of performing thermal displacement correction by machine learning in a wire discharge processing machine having such a configuration, the temperature difference calculation unit 120 sets the temperature data of the water temperature of the processing liquid and the temperature data of the room temperature around the machine. It is good to calculate the difference. When the temperature is adjusted in a plurality of parts of the wire electric discharge machine, the temperature difference calculation unit 120 may calculate the difference in temperature data of the plurality of parts.

熱変位量取得部１３０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理と、ＰＬＣ１６、インタフェース１８等を用いた制御処理が行われることで実現される。熱変位量取得部１３０は、所定のタイミングにおいて測定されたワイヤ放電加工機の熱変位量を取得する。熱変位量取得部１３０は、上ガイド３１５及び下ガイド３１７（熱で変異する部分）と、加工槽３０２（熱で変異しない部分）との距離を測定するセンサ等を利用して、熱変位量を取得するようにしても良い。熱変位量と時刻との関係は、制御用プログラム２００の各ブロックが実行されていた時刻を参照することで容易に取得することができる。熱変位量取得部１３０が取得した熱変位量は、時刻と関連付けて学習データ記憶部２１０に記憶される。 In the thermal displacement amount acquisition unit 130, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and performs arithmetic processing mainly using the RAM 13 and the non-volatile memory 14 by the CPU 11. , PLC16, interface 18, etc. are used for control processing. The thermal displacement amount acquisition unit 130 acquires the thermal displacement amount of the wire electric discharge machine measured at a predetermined timing. The thermal displacement amount acquisition unit 130 uses a sensor or the like that measures the distance between the upper guide 315 and the lower guide 317 (the part that changes due to heat) and the processing tank 302 (the part that does not change due to heat), and uses a sensor or the like to measure the amount of thermal displacement. You may try to get. The relationship between the amount of thermal displacement and the time can be easily obtained by referring to the time when each block of the control program 200 is executed. The thermal displacement amount acquired by the thermal displacement amount acquisition unit 130 is stored in the learning data storage unit 210 in association with the time.

学習部１４０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理が行われることで実現される。学習部１４０は、温度取得部１１０が取得した温度データ及び温度差算出部１２０が算出した温度差を入力データとし、熱変位量取得部１３０が取得した熱変位量を出力データとした教師データに基づいて機械学習の処理を行う。そして、学習部１４０は、ワイヤ放電加工機の環境や各部から取得された温度データ及び該温度データから算出される温度差から、ワイヤ放電加工機の熱変位量を推定するための熱変位補正モデル（学習モデル）を作成する。学習部１４０が作成する熱変位補正モデルは、例えば以下の数２式を用いても良い。数２式において、Ｄu及びＤylそれぞれ上ガイド、下ガイドの変位量、Ｃu、Ｃw、Ｃlはそれぞれコラム３０３の上部の温度、加工槽３０２内の加工液の水温、機械周辺の室温、ａ１u〜ａ４u、ａ１l〜ａ４lはワイヤ放電加工機の種類や動作環境によって定まる係数である。 In the learning unit 140, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and the CPU 11 mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14. It is realized by. The learning unit 140 uses the temperature data acquired by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation unit 120 as input data, and the heat displacement amount acquired by the thermal displacement amount acquisition unit 130 as output data as teacher data. Machine learning processing is performed based on this. Then, the learning unit 140 is a thermal displacement correction model for estimating the thermal displacement amount of the wire discharge processing machine from the environment of the wire discharge processing machine, the temperature data acquired from each part, and the temperature difference calculated from the temperature data. Create (learning model). As the thermal displacement correction model created by the learning unit 140, for example, the following equation 2 may be used. In Equation 2, D u and D yl respectively on the guide, the displacement amount of the lower guide, C u, C w, the upper temperature of each C l a column 303, the working fluid in the machining tank 302 the water temperature, around machinery Room temperature, a1 u to a4 u , and a1 l to a4 l are coefficients determined by the type of wire electric discharge machine and the operating environment.

Figure 2021104564
Figure 2021104564

また、学習部１４０が作成する熱変位補正モデルは、例えば多層構造のニューラルネットワークなどを用いても良い。この場合においても、入力データとして各部の温度に加えて、所定の温度間の温度差を用いることで、同様の効果が期待できる。この時、例えば図６に示されるように、入力層に近い位置に配置されるノードのパラメータを調整して、入力された所定の温度の差を演算する差分演算器を構築しても良い。このようにした上で、差分演算器として働くノード以外のノードで構成されるニューラルネットワークの学習を行わせることで、やはり同様の効果が期待できる。学習部１４０が作成した学習モデルは、学習モデル記憶部２２０に記憶される。 Further, the thermal displacement correction model created by the learning unit 140 may use, for example, a neural network having a multi-layer structure. Even in this case, the same effect can be expected by using the temperature difference between predetermined temperatures in addition to the temperature of each part as input data. At this time, for example, as shown in FIG. 6, a differential calculator may be constructed by adjusting the parameters of the nodes arranged at positions close to the input layer to calculate the input predetermined temperature difference. In this way, the same effect can be expected by learning a neural network composed of nodes other than the node that works as a differential calculator. The learning model created by the learning unit 140 is stored in the learning model storage unit 220.

上記構成を備えた本実施形態による熱変位補正装置１は、ワイヤ放電加工機の環境の温度や各部の温度の温度データ及び所定の温度データの差と、ワイヤ放電加工機の熱変位量との相関性を学習した学習モデルを生成することができる。ここで生成された学習モデルは、ワイヤ放電加工機の環境の温度や各部の温度の温度データ及び所定の温度データの差から、ワイヤ放電加工機の熱変位量を推定するために用いることができる。 The thermal displacement correction device 1 according to the present embodiment having the above configuration has a difference between the temperature data of the environment of the wire discharge processing machine, the temperature data of each part, and the predetermined temperature data, and the amount of thermal displacement of the wire discharge processing machine. It is possible to generate a learning model that has learned the correlation. The learning model generated here can be used to estimate the amount of thermal displacement of the wire electric discharge machine from the difference between the temperature data of the environment of the wire electric discharge machine, the temperature of each part, and the predetermined temperature data. ..

本実施形態による熱変位補正装置１を用いて機械学習をする際には、所定の温度データの差のバリエーションを含んだデータを取得することで、様々な温度パターンにおいて精度良く熱変位量を推定できる学習モデルを作成できる。そのため、荒加工をしている場合と、仕上げ加工をしている場合や非加工時の場合との両方の場合の温度状態を測定する必要はなく、どちらか一方のデータを取得するだけで、精度良く熱変位量を推定することができる学習モデルを構築できる。これにより、機械学習時の作業者の労力を軽減できることが期待される。 When machine learning is performed using the thermal displacement correction device 1 according to the present embodiment, the amount of thermal displacement is estimated accurately in various temperature patterns by acquiring data including variations of predetermined temperature data differences. You can create a learning model that you can do. Therefore, it is not necessary to measure the temperature state in both the rough processing, the finishing processing, and the non-processing case, and it is only necessary to acquire the data of either one. A learning model that can accurately estimate the amount of thermal displacement can be constructed. This is expected to reduce the labor of workers during machine learning.

図３は、本発明の第２実施形態による熱変位補正装置１が備える機能を概略的なブロック図として示したものである。本実施形態による熱変位補正装置１が備える各機能は、図１に示した熱変位補正装置１が備えるＣＰＵ１１がシステム・プログラムを実行し、熱変位補正装置１の各部の動作を制御することにより実現される。 FIG. 3 shows a schematic block diagram of the functions provided by the thermal displacement correction device 1 according to the second embodiment of the present invention. Each function of the thermal displacement correction device 1 according to the present embodiment is obtained by the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executing a system program and controlling the operation of each part of the thermal displacement correction device 1. It will be realized.

本実施形態の熱変位補正装置１は、制御部１００、温度取得部１１０、温度差算出部１２０、推定部１５０、補正部１６０を備える。また、熱変位補正装置１のＲＡＭ１３乃至不揮発性メモリ１４には、予めワイヤ放電加工機を制御するための制御用プログラム２００が記憶されており、また、第１実施形態による学習部１４０が作成した学習モデルを記憶した学習モデル記憶部２２０が設けられている。 The thermal displacement correction device 1 of the present embodiment includes a control unit 100, a temperature acquisition unit 110, a temperature difference calculation unit 120, an estimation unit 150, and a correction unit 160. Further, a control program 200 for controlling the wire electric discharge machine is stored in advance in the RAM 13 to the non-volatile memory 14 of the thermal displacement correction device 1, and the learning unit 140 according to the first embodiment is created. A learning model storage unit 220 that stores the learning model is provided.

本実施形態による制御部１００は、機能は第１実施形態による制御部１００と同様の機能を備える。 The control unit 100 according to the present embodiment has the same function as the control unit 100 according to the first embodiment.

本実施形態による温度取得部１１０は、第１実施形態による温度取得部１１０と同様に、センサ３により測定されたワイヤ放電加工機の環境の温度や各部の温度の温度データを取得する。本実施形態による温度取得部１１０が取得した温度データは、温度差算出部１２０及び推定部１５０に出力される。 Similar to the temperature acquisition unit 110 according to the first embodiment, the temperature acquisition unit 110 according to the present embodiment acquires temperature data of the environment temperature of the wire electric discharge machine and the temperature of each part measured by the sensor 3. The temperature data acquired by the temperature acquisition unit 110 according to the present embodiment is output to the temperature difference calculation unit 120 and the estimation unit 150.

本実施形態による温度差算出部１２０は、第１実施形態による温度差算出部１２０と同様に、温度取得部１１０が取得した温度データの内で、予め設定された所定の温度データの間の差を算出する。本実施形態による温度差算出部１２０が算出した温度データの差は、算出元の温度データと関連付けて推定部１５０に出力される。 Similar to the temperature difference calculation unit 120 according to the first embodiment, the temperature difference calculation unit 120 according to the present embodiment is a difference between the preset temperature data among the temperature data acquired by the temperature acquisition unit 110. Is calculated. The difference in the temperature data calculated by the temperature difference calculation unit 120 according to the present embodiment is output to the estimation unit 150 in association with the temperature data of the calculation source.

推定部１５０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理が行われることで実現される。推定部１５０は、温度取得部１１０が取得した温度データ及び温度差算出部１２０が算出した温度差に基づいて、学習モデル記憶部２２０に記憶される学習モデルを用いた機械学習の推定処理を行う。そして、推定部１５０は、温度取得部１１０が取得した温度データ及び温度差算出部１２０が算出した温度差に基づいて、ワイヤ放電加工機の熱変位量を算出する。推定部１５０は、例えば学習モデルが数２式に例示される式である場合には、各変数に対して温度取得部１１０が取得した温度データ及び温度差算出部１２０が算出した温度差を代入することで、上ガイド及び下ガイドの熱変位量を算出する。推定部１５０は、例えば学習モデルがニューラルネットワーク等である場合には、該ニューラルネットワークに対して温度取得部１１０が取得した温度データ及び温度差算出部１２０が算出した温度差を入力し、上ガイド及び下ガイドの熱変位量を出力値として得る。そして、得られた熱変位量から補正するべき熱変位補正量を推定する。推定部１５０が推定した熱変位補正量は補正部１６０に出力される。 In the estimation unit 150, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and the CPU 11 mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14. It is realized by. The estimation unit 150 performs machine learning estimation processing using the learning model stored in the learning model storage unit 220 based on the temperature data acquired by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation unit 120. .. Then, the estimation unit 150 calculates the amount of thermal displacement of the wire electric discharge machine based on the temperature data acquired by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation unit 120. For example, when the learning model is an equation exemplified by Equation 2, the estimation unit 150 substitutes the temperature data acquired by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation unit 120 for each variable. By doing so, the amount of thermal displacement of the upper guide and the lower guide is calculated. For example, when the learning model is a neural network or the like, the estimation unit 150 inputs the temperature data acquired by the temperature acquisition unit 110 and the temperature difference calculated by the temperature difference calculation unit 120 into the neural network, and guides the above. And the amount of thermal displacement of the lower guide is obtained as the output value. Then, the thermal displacement correction amount to be corrected is estimated from the obtained thermal displacement amount. The thermal displacement correction amount estimated by the estimation unit 150 is output to the correction unit 160.

補正部１６０は、図１に示した熱変位補正装置１が備えるＣＰＵ１１が、それぞれＲＯＭ１２から読み出したシステム・プログラムを実行し、主としてＣＰＵ１１によるＲＡＭ１３、不揮発性メモリ１４を用いた演算処理が行われることで実現される。補正部１６０は、推定部１５０が推定したワイヤ放電加工機の熱変位補正量に基づいて、ワイヤ放電加工機の各軸の位置を補正するように制御部１００に指令する。 In the correction unit 160, the CPU 11 included in the thermal displacement correction device 1 shown in FIG. 1 executes a system program read from the ROM 12, respectively, and the CPU 11 mainly performs arithmetic processing using the RAM 13 and the non-volatile memory 14. It is realized by. The correction unit 160 commands the control unit 100 to correct the position of each axis of the wire electric discharge machine based on the thermal displacement correction amount of the wire electric discharge machine estimated by the estimation unit 150.

上記構成を備えた本実施形態による熱変位補正装置１は、ワイヤ放電加工機の環境の温度や各部の温度の温度データ及び所定の温度データの差に基づいて、学習モデルを用いた熱変位補正量の推定を行う。そして、推定された熱変位補正量に基づいて、ワイヤ放電加工機の各軸の位置を補正することができる。 The thermal displacement correction device 1 according to the present embodiment having the above configuration uses a learning model to correct thermal displacement based on the difference between the temperature data of the environment of the wire discharge processing machine, the temperature of each part, and the predetermined temperature data. Estimate the amount. Then, the position of each axis of the wire electric discharge machine can be corrected based on the estimated thermal displacement correction amount.

以上、本発明の一実施形態について説明したが、本発明は上述した実施の形態の例のみに限定されることなく、適宜の変更を加えることにより様々な態様で実施することができる。
上記した実施形態では、ワイヤ放電加工機の熱変位補正量を推定しているが、本願発明による熱変位補正装置は、放電加工機や、他の熱変位補正を必要とする産業機械に対して広く用いることができる。特に、産業機械の所定の部分で測定された温度の温度データが、環境温度や他の所定の部分で測定された温度を参考にして調整される構成を備えた産業機械において好適に利用することができる。 Although one embodiment of the present invention has been described above, the present invention is not limited to the examples of the above-described embodiments, and can be implemented in various embodiments by making appropriate changes.
In the above-described embodiment, the thermal displacement correction amount of the wire electric discharge machine is estimated, but the thermal displacement correction device according to the present invention is for an electric discharge machine and other industrial machines that require thermal displacement correction. Can be widely used. In particular, it is suitably used in an industrial machine having a configuration in which the temperature data of the temperature measured in a predetermined part of the industrial machine is adjusted with reference to the environmental temperature and the temperature measured in another predetermined part. Can be done.

１ 熱変位補正装置
３ センサ
１１ ＣＰＵ
１２ ＲＯＭ
１３ ＲＡＭ
１４ 不揮発性メモリ
１５，１７，１８ インタフェース
１６ ＰＬＣ
１９ Ｉ／Ｏユニット
２２ バス
３０ 軸制御回路
４０ サーボアンプ
５０ サーボモータ
７０ 表示装置
７１ 入力装置
７２ 外部機器
１００ 制御部
１１０ 温度取得部
１２０ 温度差算出部
１３０ 熱変位量取得部
１４０ 学習部
１５０ 推定部
２００ 制御用プログラム
２１０ 学習データ記憶部
２２０ 学習モデル記憶部 1 Thermal displacement compensator 3 Sensor 11 CPU
12 ROM
13 RAM
14 Non-volatile memory 15, 17, 18 Interface 16 PLC
19 I / O unit 22 Bus 30 Axis control circuit 40 Servo amplifier 50 Servo motor 70 Display device 71 Input device 72 External device 100 Control unit 110 Temperature acquisition unit 120 Temperature difference calculation unit 130 Thermal displacement amount acquisition unit 140 Learning unit 150 Estimator unit 200 Control program 210 Learning data storage 220 Learning model storage

Claims (4)

複数の機械要素が組み合わされて構成される機械の熱変位を補正する熱変位補正に係る機能を有する熱変位補正装置であって、
前記機械が設置された環境の温度及び前記機械の各部の温度を測定する温度取得部と、
前記機械の熱変位量を取得する熱変位量取得部と、
前記温度取得部が測定した温度の内で、少なくとも２つの温度の温度差を算出する温度差算出部と、
前記温度取得部が測定した温度と、前記温度差算出部が算出した温度差とを入力データとし、前記熱変位量取得部が取得した熱変位量を出力データとする教師データに基づいて、前記入力データから前記出力データを推定する熱変位補正モデルを機械学習により作成する学習部と、
を備えた熱変位補正装置。 It is a thermal displacement correction device having a function related to thermal displacement correction that corrects the thermal displacement of a machine composed of a combination of a plurality of machine elements.
A temperature acquisition unit that measures the temperature of the environment in which the machine is installed and the temperature of each part of the machine,
A thermal displacement amount acquisition unit that acquires the thermal displacement amount of the machine,
A temperature difference calculation unit that calculates a temperature difference between at least two temperatures among the temperatures measured by the temperature acquisition unit, and a temperature difference calculation unit.
The temperature measured by the temperature acquisition unit and the temperature difference calculated by the temperature difference calculation unit are used as input data, and the heat displacement amount acquired by the heat displacement amount acquisition unit is used as output data. A learning unit that creates a thermal displacement correction model that estimates the output data from input data by machine learning,
Thermal displacement compensator equipped with. 複数の機械要素が組み合わされて構成される機械の熱変位を補正する熱変位補正機能を有する熱変位補正装置であって、
前記機械が設置された環境の温度及び前記機械の各部の温度を測定する温度取得部と、
を取得する熱変位量取得部と、
前記温度取得部が測定した温度の内で少なくとも２つの温度の温度差を算出する温度差算出部と、
前記機械が設置された環境の温度及び前記機械の各部の温度と、前記環境の温度及び前記機械の各部の温度の内で少なくとも２つの温度から算出された温度差とを入力データとし、前記機械の熱変位量を出力データとする教師データに基づいて機械学習をすることで作成された熱変位補正モデルを記憶する学習モデル記憶部と、
前記温度取得部が測定した温度と、前記温度差算出部が算出した温度差とに基づいて、前記学習モデル記憶部に記憶される熱変位補正モデルを用いた前記機械の熱変位量の推定をする推定部と、
前記推定部の推定結果に基づいて、前記機械の熱変位を補正する補正部と、
を備えた熱変位補正装置。 It is a thermal displacement correction device having a thermal displacement correction function that corrects the thermal displacement of a machine composed of a combination of a plurality of machine elements.
A temperature acquisition unit that measures the temperature of the environment in which the machine is installed and the temperature of each part of the machine,
The thermal displacement amount acquisition unit to acquire
A temperature difference calculation unit that calculates a temperature difference between at least two temperatures among the temperatures measured by the temperature acquisition unit, and a temperature difference calculation unit.
The temperature of the environment in which the machine is installed, the temperature of each part of the machine, and the temperature difference calculated from at least two temperatures within the temperature of the environment and the temperature of each part of the machine are used as input data, and the machine is used. A learning model storage unit that stores the thermal displacement correction model created by machine learning based on the teacher data that uses the thermal displacement amount of
Based on the temperature measured by the temperature acquisition unit and the temperature difference calculated by the temperature difference calculation unit, the thermal displacement amount of the machine is estimated using the thermal displacement correction model stored in the learning model storage unit. And the estimation part to do
A correction unit that corrects the thermal displacement of the machine based on the estimation result of the estimation unit,
Thermal displacement compensator equipped with. 前記機械やワイヤ放電加工機であり、
前記温度差算出部は、前記ワイヤ放電加工機の加工槽の加工液の温度とその他のいずれかの温度との差である、
請求項１又は２に記載の熱変位補正装置。 The machine or wire electric discharge machine
The temperature difference calculation unit is the difference between the temperature of the processing liquid in the processing tank of the wire electric discharge machine and any other temperature.
The thermal displacement correction device according to claim 1 or 2. 前記その他のいずれかの温度は、前記加工液の温度を調整する際に参照する先の温度である、
請求項３に記載の熱変位補正装置。 The other temperature is the temperature to be referred to when adjusting the temperature of the processing liquid.
The thermal displacement correction device according to claim 3.
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